A commitment has been made in the U.S. to search for more effective methods of providing health care through the better management of health resources. In part as a result of this commitment health care organizations have turned to the use of outpatient facilities as an answer to the growing strain on the health care system. The management problem in an outpatient setting lies along several dimensions-personnel, plant, patients, and processes - and along any of those dimensions spans the time horizon of long-term, intermediate-term, and short-term decisions. This problem has been complicated by the introduction of physician's assistants into ambulatory health care settings. Work to date dealing with the planning problems of outpatient settings primarily has used either linear programming or computer simulation. The linear programs, however, are rather severe abstractions of reality. On the other hand, the simulations are more realistic, but they are very expensive and do not necessarily identify optimal solutions to the planning problem. In the proposed work a recursive optimization-simulation approach is used to take advantage of the good features of both methods while minimizing the disadvantages of each method used by itself. The optimization model, a mixed integer program, is used to generate staffing and facility plans for the practice, thus reducing the number of alternatives requiring analysis by the simulation. The simulation model then evaluates the feasibility of these plans by considering more detailed information (such as possible triage policies, delegation policies, and scheduling algorithms) and other complex relationships omitted from the optimization model. If the plans prove to be infeasible, the simulation output is put into a linear regression to determine new constraints to be added to the optimization model. Two case studies will be used to test the new approach.